APPLICATION OF COMPRESSIVE SAMPLING FOR CIVIL SHTRUCTRAL HEALTH MONITORING

被引：0

作者：

Bao, Yuequan ^{[1
]}

Li, Hui ^{[1
]}

Ou, Jinping ^{[2
]}

机构：

[1] Harbin Inst Technol, Sch Civil Engn, Harbin 150090, Peoples R China

[2] Dalian Univ Technol, Sch Civil & Hydraul Engn, Dalian 116024, Peoples R China

来源：

PROCEEDINGS OF THE TWELFTH INTERNATIONAL SYMPOSIUM ON STRUCTURAL ENGINEERING, VOLS I AND II | 2012年

基金：

中国博士后科学基金;

关键词：

Compressive sampling; structural health monitoring; lost data recovery; moving loads distribution identification;

D O I：

暂无

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

Compressive sampling also called compressive sensing (CS) is a novel information theory proposed recently. CS provides a new sampling theory to reduce data acquisition, which says that sparse or compressible signals can be exactly reconstructed from highly incomplete random sets of measurements. CS broke through the restrictions of the Shannon theorem on the sampling frequency, which can use fewer sampling resources, higher sampling rate and lower hardware and software complexity to obtain the measurements. Not only for data acquision, CS also can be used to find the sparse solutions for linear algebraic equation problem. In this paper, the applications of CS for SHM are presented including acceleration data acquisition, lost data recovery for wireless sensor and moving loads distribution identification. The investigation results show that CS has remarkable advanges for the sparse inverse problem which has good potential in SHM.

引用

页码：1553 / 1558

页数：6